We noticed you're browsing in private or incognito mode.

To continue reading this article, please exit incognito mode or log in.

Not an Insider? Subscribe now for unlimited access to online articles.

Rewriting Life

Genome Study Targets African Americans

Howard University researchers are looking for genetic clues about the high incidence of some diseases among black Americans.

The first genome-wide scan of an African-American population is under way, as scientists look for genetic clues about diseases such as obesity, hypertension, and diabetes in the population group. These diseases, says Charles Rotimi, an epidemiologist at Howard University, have higher rates of incidence in African Americans compared with European Americans. With this study, he hopes to identify the genetic factors that may contribute to these higher incidence rates.

Rotimi and Michael Christman, a geneticist at Boston University School of Medicine, plan to sample the DNA of 1,500 African Americans in the Washington, D.C. area. They will then look for key genetic differences between individuals who are, for example, obese and not obese. Small alterations in the genetic code, if shared by a significant number in the sample of overweight individuals, could serve as genetic markers for obesity.

One goal of the study is to better understand how the complex interactions of genetics and environmental factors lead to the high incidences of the diseases. In previous work, Rotimi, director of the National Human Genome Center at Howard University, has found that hypertension rates vary widely in populations with African ancestry, depending on where such people now live. That is, black populations in rural West Africa show a low rate of hypertension (7 percent). Those in the Caribbean have significantly higher incidences (28 percent), while African Americans have even higher incidences (34 percent). The difference, Rotimi suspects, is a combination of a person’s environment and genetics, and he hopes that the genome-wide scan will provide important clues about the contribution of each.

That’s where Michael Christman comes in. Christman, chair of the Genetics and Genomics Department at Boston University, recently identified specific regions of the genome associated with obesity in a sample mainly of European Americans. After scanning the genomes of 1,320 people–participants in a long-running, multigenerational study called the Framingham Heart Study–he found that those who were obese shared common variations in their DNA.

Christman and Rotimi hope to similarly identify DNA variations in African Americans that may code them for a propensity toward obesity, hypertension, and diabetes. The researchers plan to analyze blood samples from the Washington, D.C., group using the latest in gene-chip technology from Affymetrix, a leading genetic microarray company. The gene-chip technology maps highly dense and complex regions of DNA. Researchers will use the chip to finely map specific areas of the genome in search of meaningful variations.

“Even though the increase in obesity has an environmental cause–for example, caloric excess and sedentary behavior–that environment is laid down on a foundation of genetics, which is at least half of your propensity for obesity,” says Christman. “It’s sort of a set point, a high and low range for an individual [propensity] for obesity.”

To tease out the genetic component of obesity, Christman and Rotimi will be looking for shared single nucleotide polymorphisms (SNPs) among obese versus non-obese African Americans. It’s a potentially daunting feat: there are an estimated 10 million common SNPs known to exist, and comparing each and every variation against that of every subject would be a computational nightmare. Therefore, the team will zero in on 20 specific genes associated with the diseases it plans to study, and will map the SNPs in those particular genomic regions. Eventually, researchers will compare their results with samples from the Framingham group, and they also hope to do similar comparisons with other ethnic and geographic populations.

“The main payoff of genetics is not being able to test people and predict who will become overweight,” says Christman. “It’s in understanding the pathways that influence human obesity, so if we understand what the genes are, the future holds promise for making somewhat more intelligent drug targets for obesity.”

Troy Duster, a sociologist at New York University, offers a note of caution. Duster, author of Backdoor to Eugenics, warns that the study of the genetics of a specific race can be easily misunderstood. While the Howard University study is aiming to determine the reasons for the disproportionately high incidence of obesity in African Americas, he warns that the public can misinterpret it as, for example, a hunt for a “black obesity gene.”

Down the line, Christman and Rotimi plan to perform similar genetic scans on other populations. The long-term goal, they say, is to treat patients according to the individual’s genetic profile. Their current work will make this goal that much more attainable.

Be the leader your company needs. Implement ethical AI.
Join us at EmTech Digital 2019.

Register now
More from Rewriting Life

Reprogramming our bodies to make us healthier.

Want more award-winning journalism? Subscribe to Insider Plus.
  • Insider Plus {! insider.prices.plus !}*

    {! insider.display.menuOptionsLabel !}

    Everything included in Insider Basic, plus the digital magazine, extensive archive, ad-free web experience, and discounts to partner offerings and MIT Technology Review events.

    See details+

    Print + Digital Magazine (6 bi-monthly issues)

    Unlimited online access including all articles, multimedia, and more

    The Download newsletter with top tech stories delivered daily to your inbox

    Technology Review PDF magazine archive, including articles, images, and covers dating back to 1899

    10% Discount to MIT Technology Review events and MIT Press

    Ad-free website experience

You've read of three free articles this month. for unlimited online access. You've read of three free articles this month. for unlimited online access. This is your last free article this month. for unlimited online access. You've read all your free articles this month. for unlimited online access. You've read of three free articles this month. for more, or for unlimited online access. for two more free articles, or for unlimited online access.